Recently the quantity of image data for medical image diagnosis has been drastically improved due to the development of imaging technique of medical image diagnostic apparatuses (modality) such as X-ray CT and MRI.
As for X-ray CT apparatuses, multi-slice CT that arranges a detector in a body axis direction of an object to be examined, or cone beam CT using a detector in which the detection elements are two-dimensionally arranged have become widely used, which enabled imaging tomograms of the wide range portion. In other words, in these multi-slice CT or cone beam CT, quantity of image data has improved drastically due to the addition of a dimension that is a body axis of the object to a two-dimensional tomogram of the object by conventional single-slice CT that makes it three-dimensional.
Also as for MRI apparatus, techniques for high-speed imaging such as a parallel imaging method have become widely used. Since MRI apparatus collects three-dimensional information from the beginning, the quantity of image data will increase by speeding up the collection of three-dimensional image information.
Image readers have been in desperate need of the development of an effective interpretation method for the above-mentioned large amount of image data. Given this factor, one of the methods being developed is CAD (Computer Aided Detection) for detecting abnormal shadow (hereinafter the term “shadow” is treated as synonym of the term “nodule”) candidates by making a computer execute a prescribed image recognition process in relation to a plurality of medical images of an object imaged by modality.
Heretofore, as described in “Image Diagnosis Supporting System” of Patent Document 1, CAD superposes a detected abnormal shadow candidate and a marker such as a circle or arrow and displays it on display means in order to indicate the detected abnormal shadow candidate on images of the object.
In the meantime, there are shadows that are not actually abnormal called “false-abnormal shadow” among the abnormal shadow candidates being detected by the above-mentioned CAD, and image readers who carry out the image diagnosis need to differentiate them by their own interpretation and eliminate the discriminated false-abnormal shadows from the abnormal shadow candidates.
Patent Document 1: JP-A-2002-325761
However, the technique of Patent Document 1 includes various deficiencies and disadvantages, such as, for example, the following.    (1) There is no display of the reasons for detection of the abnormal shadow candidates being detected by the above-mentioned CAD.    (2) There is not enough information about the images including the abnormal shadow candidates being detected by the above-mentioned CAD. For example, in a case that the image is one tomogram, no vicinal information of the image thereof is presented.
Stated another way, image readers have to determine the reasons for detection or its vicinal information based on the knowledge from their own experiences, for example, whether the abnormal shadow is false-positive or not, or the condition of the vicinity of the region being imaged based on their anatomical knowledge. As a result, a good amount of time is required of the image readers to determine the above-mentioned issues, and especially for rather inexperienced readers some extra time in seeking the advice of experienced ones for the above-mentioned determinations.
Because of such background, a method to support the above-mentioned determination is strongly desired by image readers.
In an aspect of this disclosure, there is provided an image diagnosis supporting system that comprises:                image data reading means for reading in image data presenting the image of an object to be examined being obtained by a medical imaging apparatus;        abnormal shadow candidate detecting means for detecting abnormal shadow candidates satisfying at least one of a plurality of criteria for abnormal shadow criteria from the read-in images; and        display means for superposing and displaying the read-in images and markers indicating the detected abnormal shadow candidates,        wherein the image diagnosis supporting system is further provided with:        setting means for setting the criteria to support the determination of the abnormal shadow candidates being detected by the abnormal shadow candidate detecting means as the determination-supporting criteria; and        control means for causing the display means to display the set determination-supporting criteria, the abnormal shadow candidate and the marker simultaneously.        
Accordingly, an image diagnosis support system to give a support to the effective determination of the type of abnormal shadow candidates can be provided.
In another aspect of this disclosure, there is provided an image diagnosis supporting method that includes:                an image data reading step for reading in the image data representing an image of an object to be examined being obtained by a medical imaging apparatus;        an abnormal shadow candidate detecting step for detecting abnormal shadow candidates satisfying at least one of a plurality of criteria for abnormal shadow from the read-in images;        a step for setting the criteria for supporting the determination of the detected abnormal shadow candidates as the determination-supporting criteria; and        a display step for displaying this set determination-supporting criteria, the read-in images and the marker indicating the detected abnormal shadow candidate simultaneously.        
Accordingly, an image diagnosis support method that can support an effective determination of the type of abnormal shadow candidates can be provided.
When the techniques of this disclosure are applied, the type of abnormal shadow candidates can be determined more effectively by the determination-supporting criteria.